24 hours ago
Base Salary
$200k - $260k/yr
Responsibilities
- Build predictive models on large-scale clinical data for risk stratification, utilization prediction, and care-gap detection.
- Own the full ML lifecycle, including problem framing, feature engineering, training, evaluation, deployment, and production monitoring.
- Convert unstructured clinical data such as PDFs, images, and doctors’ notes into structured records.
- Build training and inference pipelines, experiment tracking, model versioning, and evaluation infrastructure.
- Collaborate with founders, engineers, and customers to identify and prioritize high-leverage ML problems.
- Operate production ML systems and monitor for drift, degradation, reliability, and measurable outcomes.
Requirements
- 7+ years of experience building ML systems that run against real data at scale.
- Strong knowledge of regression, tree-based methods, feature engineering, dimensionality reduction, and deep learning, with hands-on model-building and training experience.
- Demonstrated record of delivering measurable ML results in production.
- Strong software engineering fundamentals and experience building or operating large-scale cloud backend systems, ideally on AWS.
- Ability to own training pipelines, model serving, monitoring, SQL, large datasets, and data pipelines end to end.
- Located in San Francisco or the Bay Area, or willing to relocate.
- Preferred experience with healthcare standards and technologies including FHIR, HIE, IHE, EHR/EMR, NPI, TEFCA, ADT, HL7, HEDIS, RAF, SNOMED, LOINC, and ICD-10.
- Founder experience or experience as the first or only ML hire at an early-stage startup is preferred.
Benefits
- Competitive equity and compensation package.
- Full family Platinum health, dental, and vision insurance.
- 401(k) retirement plan with matching.
- Flexible work-from-home or in-office arrangement.
- Complimentary healthy lunches when working in-office, with breakfast and dinners as needed.
- Quarterly company off-sites.
- Company-provided MacBook.
- Unlimited PTO.
- Leaders are in the office six days per week and the team is generally expected to be available six days per week.
Tech Stack
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